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X In most instances, this position requires in-person interviews as part of the hiring process.Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Mountain View, CA, USA; New York, NY, USA.
Minimum qualifications: - Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience integrating generative AI tools or LLM interfaces into workflows.
Preferred qualifications: - Experience with AI/ML systems, particularly with Large Language Models (LLMs) and agentic systems.
- Experience with system design, evaluation methodologies, and quantitative data analysis.
- Understanding of agentic architectures, including loops, skills, context management, planning, tool use, evals.
- Ability to work in a small-team/startup, building new products and dealing with uncertainty and fluidity.
- Passion for developer tools, code AI, design AI, developer productivity, and improving software engineering workflows.
About the jobIndividual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Design Minimum Viable Tests and prototypes to de-risk novel AI concepts. Execute technical spikes within short, iterative sprints to resolve architectural hurdles and prove core feasibility.
- Apply deep expertise in agentic systems-planning, memory, context, tool-use, and loops-to build novel design, coding, and product solutions.
- Blend Software Engineering with Product Management, Research, Data Science, UX Research functions and an entrepreneurial mindset.
- Analyze early technical and user signals to evaluate project feasibility and inform decisions. Prioritize rapid validation and learning; test for user and value, and technical feasibility to gather actionable signal before committing to scaled infrastructure.
- Grow in highly fluid, 0-to-1 environments. Partner closely within small, cross-functional teams to transform raw, ambiguous ideas into concrete technical and product directions.
